2024
Tensor dictionary-based heterogeneous transfer learning to study emotion-related gender differences in brain
Yang L, Qiao C, Kanamori T, Calhoun V, Stephen J, Wilson T, Wang Y. Tensor dictionary-based heterogeneous transfer learning to study emotion-related gender differences in brain. Neural Networks 2024, 183: 106974. PMID: 39657530, DOI: 10.1016/j.neunet.2024.106974.Peer-Reviewed Original ResearchFeature spaceClassification performanceHeterogeneous transfer learningTensor dictionary learningHeterogeneous knowledge sharingTransfer learning frameworkReduce training costsDictionary learningKnowledge sharing strategyHeterogeneous transferGender classificationTransfer learningLearning frameworkConnectivity dataHeterogeneous dataHeterogeneous knowledgeBrain activity dataPriori knowledgeTraining costsSharing strategyProblem of insufficient sample sizeKnowledge sharingEEG dataExperimental resultsDictionary
2022
Federated Transfer Learning for Low-Dose PET Denoising: A Pilot Study With Simulated Heterogeneous Data
Zhou B, Miao T, Mirian N, Chen X, Xie H, Feng Z, Guo X, Li X, Zhou S, Duncan J, Liu C. Federated Transfer Learning for Low-Dose PET Denoising: A Pilot Study With Simulated Heterogeneous Data. IEEE Transactions On Radiation And Plasma Medical Sciences 2022, 7: 284-295. PMID: 37789946, PMCID: PMC10544830, DOI: 10.1109/trpms.2022.3194408.Peer-Reviewed Original ResearchLow-dose PETMedical data privacy regulationsFederated learning algorithmLarge domain shiftTransfer learning frameworkData privacy regulationsHigh-quality reconstructionFederated transferData privacyHeterogeneous dataDomain shiftLearning frameworkLearning algorithmPrivacy regulationsData distributionCollaborative trainingLow-dose dataPET reconstructionPrevious methodsFL methodEfficient wayLocal dataSuperior performanceExperimental resultsDenoising
2021
The application of artificial intelligence and data integration in COVID-19 studies: a scoping review
Guo Y, Zhang Y, Lyu T, Prosperi M, Wang F, Xu H, Bian J. The application of artificial intelligence and data integration in COVID-19 studies: a scoping review. Journal Of The American Medical Informatics Association 2021, 28: 2050-2067. PMID: 34151987, PMCID: PMC8344463, DOI: 10.1093/jamia/ocab098.Peer-Reviewed Original ResearchConceptsAI applicationsArtificial intelligenceData integrationHeterogeneous dataSocial media data analysisMost AI applicationsHeterogeneous data sourcesMedia data analysisProteomics data analysisAI algorithmsAI frameworkElectronic health recordsHeterogenous dataBiased algorithmsHealth recordsCOVID-19 researchData analysisSingle-source approachResearch topicData sourcesResearch areaIntelligenceSurveillance systemDifferent sourcesAlgorithm
2012
SHARE: system design and case studies for statistical health information release
Gardner J, Xiong L, Xiao Y, Gao J, Post A, Jiang X, Ohno-Machado L. SHARE: system design and case studies for statistical health information release. Journal Of The American Medical Informatics Association 2012, 20: 109-116. PMID: 23059729, PMCID: PMC3555328, DOI: 10.1136/amiajnl-2012-001032.Peer-Reviewed Original ResearchConceptsDifferential privacy frameworkPrivacy frameworkDifferential privacyMultidimensional histogramsReal medical datasetsMedical data warehouseOriginal data distributionInformation releaseHigh-dimensional dataBreast cancer datasetPattern queriesMedical datasetsElectronic medical record datasetHeterogeneous dataData warehouseUse casesElectronic health recordsMedical domainBiomedical dataThree-dimensional data cubeArt methodsData distributionMedical dataDimensional dataData cube
2002
Senselab: Modeling Heterogenous Data on the Nervous System
Nadkarni P, Mirsky J, Skoufos E, Healy M, Hines M, Miller P, Shepherd G. Senselab: Modeling Heterogenous Data on the Nervous System. 2002, 105-118. DOI: 10.1007/0-306-46903-0_10.Peer-Reviewed Original Research
2001
Integration of Multidisciplinary Sensory Data
Miller P, Nadkarni P, Singer M, Marenco L, Hines M, Shepherd G. Integration of Multidisciplinary Sensory Data. Journal Of The American Medical Informatics Association 2001, 8: 34-48. PMID: 11141511, PMCID: PMC134590, DOI: 10.1136/jamia.2001.0080034.Peer-Reviewed Original ResearchConceptsNeuroinformatics researchFlexible data modelDiverse heterogeneous dataHuman Brain ProjectNew informatics technologiesHeterogeneous dataData modelSensory dataRelated toolsInformatics technologiesBrain ProjectBuilding databaseSingle unifying frameworkUnifying frameworkProject approachIntegrationComputer model
1999
Organization of Heterogeneous Scientific Data Using the EAV/CR Representation
Nadkarni P, Marenco L, Chen R, Skoufos E, Shepherd G, Miller P. Organization of Heterogeneous Scientific Data Using the EAV/CR Representation. Journal Of The American Medical Informatics Association 1999, 6: 478-493. PMID: 10579606, PMCID: PMC61391, DOI: 10.1136/jamia.1999.0060478.Peer-Reviewed Original ResearchConceptsEAV/CRHeterogeneous scientific dataPhysical database schemaStorage of dataInterobject relationshipsDatabase schemaHeterogeneous dataMedical domainComplex objectsScientific domainsClinical patient recordsSchemaBiomedical databasesRepresentationScientific dataPatient recordsSuch purposesDatabaseValue representationDomainObjectsParadigmData
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